Masterarbeit FS24

Evaluating the Effectiveness of CTA Trend Following Strategies:

A Comparative Analysis against State-of-the-Art MA-Crossing Strategies

by Raphael Nussbaumer

1. Import Libraries

2. Data

Data Description

Making own DataFrames to delete the NA's

Check which Future is younger than 1999 and drop these

Correlations

Calculate the daily returns, annualized return and the annulized volatility

Create a Summary for the statistics

Data visualisation

3. Constructing the different Trend following Methods

1. Simple moving average crossover

Calculate the simple moving average

Creating the signal and indicate the trades

2. Simple moving average crossover with 1% band

Calculate the simple moving average

Creating the signal and indicate the trades

3. Time-series momentum

Calculate the-time series momentum

Creating the signal and indicate the trades

4. Risk-adujsted time series momentum

Calculate the risk-adjusted time series momentum

Creating the signal and indicate the trades

5. Kalman filter

Calculate the Kalman filter

Creating the signal and indicate the trades

4. Building portfolios and backtester

Initializing each Strategy

Define the start date and the initial value

1. SMA

Plot each MA strategy on its own

2. SMA with Bands

Plot each MA strategy on its own

3. TSMOM

Plot each MA strategy on its own

4. RAMOM

Plot each MA strategy on its own

5. Kalman Filter

Plot each MA strategy on its own

5. Building Portfolios

Equal weighted

1. SMA

2. SMA with Bands

3. TSMOM

4. RAMOM

5. Kalman filter

Volatility weighted

1. SMA

2. SMA with Bands

3. TSMOM

4. RAMOM

5. Kalman filter

6. Comparison

SPY

BarclyHedgeCTA Index

All equal weighted portfolios

Volatility weighted Portfolios vs BarclayHedge CTA Index

Subperiods

Early 2000s recession - 01.03.2001 - 30.11.2001

Great Recession - 01.12.2007 - 30.06.2009

Covid - 19 recession - 01.02.2020 - 30.04.2020